It is best to create a figure of a right size in the first place.
If this cannot be done, try something like below.
dpi = 80
fig=figure(1, dpi=dpi)
ax = axes((0,0,1,1))
ax.set_aspect(1)
from matplotlib.transforms import TransformedBbox, Affine2D
w, h = fig.get_size_inches()
bbox = TransformedBbox(ax.bbox,
fig.transFigure.inverted()+Affine2D().scale(w, h))
savefig("a.png", bbox_inches=bbox, dpi=dpi)
Note that the size of the output will be different from the original
figure size.
Regards,
-JJ
On Tue, Feb 23, 2010 at 3:37 PM, Bruce Ford <[email protected]> wrote:
> I'm attempting to output an image with a predictable bounding box so
> that it can be placed into a KML document and be correctly
> georeferenced.
>
> Essentially I need a PNG that has NO labeling and the size of the
> image be exactly the size of the plot bounding box and no more, no
> less.
>
> I can get exactly what I want with the top and bottom of the image with:
>
> fig.add_axes((0,0,1,1)
>
> However, I'm still left with undesired space on the left and right.
> How can I bring the left and right edges of the bounding box to match
> the image width?
>
> Also, this might be a candidate for a handy function for
> pyplot.figure(). This could be very useful for anyone needing to make
> KML-friendly figures.
>
> Thanks for any ideas!
>
> Bruce
> ---------------------------------------
> Bruce W. Ford
> Clear Science, Inc.
> [email protected]
> http://www.ClearScienceInc.com
> Phone/Fax: 904-379-9704
> 8241 Parkridge Circle N.
> Jacksonville, FL 32211
> Skype: bruce.w.ford
> Google Talk: [email protected]
>
> ------------------------------------------------------------------------------
> Download Intel® Parallel Studio Eval
> Try the new software tools for yourself. Speed compiling, find bugs
> proactively, and fine-tune applications for parallel performance.
> See why Intel Parallel Studio got high marks during beta.
> http://p.sf.net/sfu/intel-sw-dev
> _______________________________________________
> Matplotlib-users mailing list
> [email protected]
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
------------------------------------------------------------------------------
Download Intel® Parallel Studio Eval
Try the new software tools for yourself. Speed compiling, find bugs
proactively, and fine-tune applications for parallel performance.
See why Intel Parallel Studio got high marks during beta.
http://p.sf.net/sfu/intel-sw-dev
_______________________________________________
Matplotlib-users mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/matplotlib-users